Femtosecond pulsed laser photodynamic therapy activates melanin and eradicates malignant melanoma
Bibliographic record
Abstract
Photodynamic therapy (PDT) relies on a series of photophysical and photochemical reactions leading to cell death. While effective for various cancers, PDT has been less successful in treating pigmented melanoma due to high light absorption by melanin. Here, this limitation is addressed by 2-photon excitation of the photosensitizer (2p-PDT) using ~100 fs pulses of near-infrared laser light. A critical role of melanin in enabling rather than hindering 2p-PDT is elucidated using pigmented and non-pigmented murine melanoma clonal cell lines in vitro. The photocytotoxicities were compared between a clinical photosensitizer (Visudyne) and a porphyrin dimer (Oxdime) with ~600-fold higher σ 2p value. Unexpectedly, while the 1p-PDT responses are similar in both cell lines, 2p activation is much more effective in killing pigmented than non-pigmented cells, suggesting a dominant role of melanin 2p-PDT. The potential for clinical translational is demonstrated in a conjunctival melanoma model in vivo, where complete eradication of small tumors was achieved. This work elucidates the melanin contribution in multi-photon PDT enabling significant advancement of light-based treatments that have previously been considered unsuitable in pigmented tumors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".